Publicação Contínua
Sociodemographic factors associated with academic goals in university students in times of the COVID-19 pandemic
Fatores sociodemográficos associados a objetivos acadêmicos em estudantes universitários em tempos de pandemia COVID-19
Factores sociodemográficos asociados a las metas académicas en estudiantes universitarios en tiempos de pandemia COVID-19
Sociodemographic factors associated with academic goals in university students in times of the COVID-19 pandemic
Revista Tempos e Espaços em Educação, vol. 14, núm. 33, e15114, 2021
Universidade Federal de Sergipe
Recepción: 11 Octubre 2020
Aprobación: 12 Enero 2021
Publicación: 21 Enero 2021
Abstract: Motivational processes in students are oriented to the fulfillment of academic goals, therefore, it is one of the significant variables of the study, for this, a student-centered approach was adopted. The present research set out to determine the association of sociodemographic factors with the academic goals of university students from a private university; The sample consisted of 1,400 students from the Health career: 659 (47.1%) were male and 741 (52.9%) were female; The approach was quantitative, of the substantive type, descriptive level, under the non-experimental cross-sectional design; a sociodemographic record was used. Regarding academic goals, the CMA questionnaire was administered. The results showed that the academic goals are associated with the variables sex, age, school of origin and hours of study of the students who participated, since the significance was p <0.05. The data obtained allowed to qualify and quantify the importance of motivation as a transcendent component for the fulfillment of the proposed objectives.
Keywords: Sociodemographic factors, Academic goals, University students.
Resumo: Os processos motivacionais nos alunos são orientados para o cumprimento dos objetivos acadêmicos, portanto, é uma das variáveis significativas do estudo, para isso, foi adotada uma abordagem centrada no aluno. A presente pesquisa teve como objetivo verificar a associação de fatores sociodemográficos com os objetivos acadêmicos de estudantes universitários de uma universidade privada; A amostra foi composta por 1.400 alunos da carreira da Saúde: 659 (47,1%) eram do sexo masculino e 741 (52,9%) do feminino; A abordagem foi quantitativa, do tipo substantivo, nível descritivo, sob o delineamento transversal não experimental; foi utilizado um registro sociodemográfico. Em relação aos objetivos acadêmicos, o questionário CMA foi aplicado. Os resultados mostraram que os objetivos acadêmicos estão associados às variáveis sexo, idade, escola de origem e horário de estudo dos alunos participantes, visto que a significância foi p <0,05. Os dados obtidos permitiram qualificar e quantificar a importância da motivação como componente transcendente para o cumprimento dos objetivos propostos.
Palavras-chave: Fatores sociodemográficos, Objetivos acadêmicos, Estudantes universitários.
Resumen: Los procesos motivacionales en los estudiantes están orientados al cumplimiento de las metas académicas, por lo tanto, es una de las variables significativas del estudio, para ello se adoptó un enfoque centrado en el estudiante. La presente investigación se propuso determinar la asociación de factores sociodemográficos con las metas académicas de estudiantes universitarios de una universidad privada; La muestra estuvo formada por 1.400 estudiantes de la carrera de Salud: 659 (47,1%) eran hombres y 741 (52,9%) eran mujeres; El abordaje fue cuantitativo, de tipo sustantivo, nivel descriptivo, bajo el diseño transversal no experimental; se utilizó un registro sociodemográfico. En cuanto a las metas académicas, se aplicó el cuestionario CMA. Los resultados mostraron que las metas académicas están asociadas con las variables sexo, edad, escuela de origen y horas de estudio de los estudiantes que participaron, ya que la significancia fue p <0.05. Los datos obtenidos permitieron calificar y cuantificar la importancia de la motivación como componente trascendente para el cumplimiento de los objetivos propuestos.
Palabras clave: Factores sociodemográficos, Metas académicas, Estudiantes universitarios.
INTRODUCTION
The health crisis caused by the COVID-19 pandemic has had repercussions in all sectors of the country, mainly in the health and education sectors; for this reason, universities have had to adapt their study plan to the new regulations with an educational modality that implies significant changes in the way they offer a better quality service or how they motivate students to meet academic goals. Education, in general, is going through difficult times; however, it has been an opportunity for change and the beginning of new paradigms. A joint ECLAC/UNESCO study (2020) indicates that COVID-19 caused havoc, affecting different socioeconomic, health, psychological and educational structures.
In addition, Pintrich (2003) stated that the goals should be resolved with more empirical research; he proposes that future research should go beyond the simplistic and mutually exclusive differentiation between learning goals (good) and performance goals (bad), in addition to contemplating the perspective of multiple goals since students can pursue more than one within their learning process (Suárez, et al., 2001). Learning or mastery goals would be most beneficial in elementary grades, showing a positive relationship with academic performance (Paulick et al., 2013); but they would lose weight in high school and college, where relationships would be weaker. These results are of great relevance because of the close relationships that motivational variables maintain with other constructs such as learning strategies or prosocial behavior in some educational stages (Inglish et al., 2013).
On the other hand, motivation and learning are different processes that have a close link between them because motivation is learned and learning does not occur independently of motivation, so much so that, in recent years, more explanatory models and didactic applications are being proposed that consider these two processes together (Rodríguez & Huertas, 2017).
After reviewing the literature, the contribution of this research is that the university student can combine different types of goals depending on personal factors such as age, sex, hours of study and school of origin. This implies the development of self-regulatory and motivational skills to achieve the proposed academic goals, for example, the admiration of people close to them such as parents and teachers is, without a doubt, an incentive. As pointed out by González et al. (2010), the concept of multiple goals has been approached from different perspectives such as the one focused on studying only the combination of goals of approaching learning and performance (Barron & Harackiewicz, 2001; Daniels, et al., 2008; Linnenbrink, 2005; Pintrich, 2000; Smith & Sinclair, 2005).
Socio-demographic factors
Sociodemographic or personal factors, according to Gutiérrez (2015), include aspects of a personal nature, which may refer to a set of variables specific to the student such as gender, age, marital status and other university studies. Sociodemographic factors are of a personal nature associated with institutional and social variables. In the same way, in Mora's study (2015), we can see how personal factors such as sex, age, school of origin, and hours of study influence the academic goals of university students. Likewise, Pender et al. (2015) define personal factors as qualities of the individual to predict certain behavior in various situations; they are classified into biological, psychological and sociocultural personal factors.
Among the biological factors are age, body mass, strength, agility, and balance, among others. With respect to psychological factors, we find self-esteem, self-motivation and self-perception. Finally, personal socio-cultural factors that include race, ethnicity, education and socioeconomic status. Within the great variety of existing personal factors considered in this research, we find sex, hours of study, school of origin and age of the students.
Psychological theories that influence academic goals
Jean Piaget's constructivist theory of learning: the Swiss researcher states that the way we learn consists in the construction of our own experiences; that is, what we experience is seen in the light of what we have previously experienced. Piaget is recognized worldwide for his contributions to the development of evolutionary psychology, since he discovered the existence of four stages of cognitive development in children: the sensory-motor stage (from 1 to 5 years), the preoperative stage (from 2 to 7 years), the concrete operations (from 7 to 11 years) and the formal operations (12 years onwards).
Lev Vygotsky's socio-cultural theory: Soviet researcher Lev Vygotsky gave a social approach to learning. For him, society, in its totality, is a means and, at the same time, a learning tool thanks to which human beings can develop intellectually. The author considers the social environment as a key piece in the learning process.
Bandura's Social Learning Theory
It is also known as learning by observation or modeling. Throughout his research, Bandura showed to what extent learning is not something that comes from facing challenges alone; but that it takes place by being immersed in an environment where we can see what others are doing and the results others have by following certain strategies (Bandura, 2012). It focuses its study interest beyond that behavioral reductionism. He was one of the first figures to put his attention on the social field, like Lev Vygotsky with his socio-cultural theory.
Academic goals in the university context
Academic goals are the purposes people have for initiating and developing goal-oriented behaviors. Goals are considered to be the cognitive and motivational representations of future behaviors performed by college students. Motivation is an important component for the fulfillment of them. It should be noted that goal orientation, as an integrated pattern of beliefs, makes a difference in why students learn or study (Pintrich, 2000).
According to Rodríguez & Huertas (2017), action plans are strategies for achieving achievements; the results obtained can be successes or failures. During their formative life, students develop motivational factors such as autonomy and the ability to work in a group.
It is also necessary to influence the goals that students set when facing different learning situations. Although each student arrives at university with certain concepts and patterns, it is possible to design proposals from the context of the university that promote learning goals that enhance motivation, interest and enjoyment of learning and, consequently, that favor the achievement of more successful academic paths (Moreno et al., 2019).
The theoretical model on which the CMA (questionnaire that measures academic goals) is based states that goal orientations are not exclusive and can coexist, as confirmed by Barca et al. (2012); these authors state that it is a process of multiple goal management, whose combination can affect the outcome of performance in different ways. They measure the tendency of students to seek to increase their competence by acquiring and mastering new skills, knowledge, and improving performance on learning tasks.
For Gaeta (2014), the goals of students are dynamic and flexible, therefore, they can be influenced; the role of the teacher as a facilitator of learning helps students learn to learn; from this conception, teachers should support them in setting learning goals and identifying self-regulatory strategies for achieving autonomous learning.
Types of academic goals versus tasks
Huertas & Agudo (2003) propose five types of goals that students can adopt when faced with academic tasks or situations:
1. Learning: the main objectives are linked to the search for knowledge, personal improvement and the improvement of their abilities. They prefer new and challenging tasks that can contribute to increase their knowledge about some subject; they also have intrinsic learning orientations so they are interested in learning and enjoy it.
2. Show off: they are interested in getting good grades, getting positive evaluations from others, being compared and standing out from their peers. Learning is not an end in itself, but the means to achieve another goal: a good image of themselves. Situations of failure or uncertainty are threats to their personal image so they prefer tasks that allow them to give a quick and, of course, correct response.
3. Avoiding failure: these students share the goal of those who seek to excel, but with a motivational tendency to avoid. They prefer to take care of their capacities and self-esteem from the negative evaluations of others so they seek to fulfill their obligations and make an effort to develop their tasks. The dangerous thing is that they avoid difficulties, they live worried and any means is valid not to fail.
4. Do not get complicated: the objective is to be at ease, calm and happy. They do not stand out for their performance, nor are they interested in it. They manage their times; they make the effort just and necessary to pass.
5. Safeguard self-esteem: their concern is to save their image, preserve and safeguard their self-esteem in front of their peers or teachers; however, they are forced to adopt attitudes that do not favor learning; for example, they do not ask for help, they sit in the back rows to go unnoticed, they do not express doubts to the teacher for fear of making a fool of themselves, among other harmful behaviors.
Dimensions of the academic goals variable
According to CMA, the dimensions of academic goals are three: learning goals, social reinforcement goals, and achievement goals.
Learning goals measure the tendency of students to seek increased competence through the acquisition and mastery of new skills and knowledge, as well as improved performance on learning tasks.
On the other hand, social reinforcement goals measure the tendency of students to learn with the purpose of obtaining approval and avoiding rejection by teachers, friends, and parents.
Finally, achievement goals measure the tendency of students to learn with the purpose of obtaining good results on tests. It will allow them to achieve their activities, goals and objectives in a timely manner.
METHODOLOGY
The focus of the study was quantitative because the data and analysis are established in a numerical way. The study corresponds to a non-experimental, cross-sectional research; according to Hernández & Mendoza (2018), they are studies that are carried out without manipulating the variables, all situations are observed in a natural environment and analyzed in a given moment. The research was of a substantive type that, as Sánchez & Reyes (2018) point out, is research oriented to solve problems that derive from social and natural reality, seeking to objectively answer the questions posed, generating a contribution to the theoretical scientific structure related to the fact under investigation. The scope of the research was descriptive since it sought to describe and, at the same time, find the association of the variables.
Instruments
A sociodemographic card was used for the independent variable (age, sex, school of origin and hours of study) prepared by the researcher. On the other hand, for the dependent variable, the questionnaire of academic goals (CMA) was used, which consists of 16 items with three dimensions: learning goals, social reinforcement goals, and achievement goals, in a scale in which each item is scored from 1 to 5, CS= Almost always; S= Always; AV= Sometimes; RV= Rarely; N= Never; Cronbach's Alpha of 0.901 showed that it is highly reliable.
Participants
The sample was made up of 1400 university students of the Health career of a private university of the first and second cycle. A random sampling was used where all students had the opportunity to be chosen. Of the 1400 students, 741 were female (52.9%) and 659 were male (47.1%); in terms of age, 691 (49.4%) were under 20 years old, 566 (40.4%) were between 21 and 22 years old, and 143 (10.2%) were over 23 years old.
Procedures
After the compilation of the theoretical support, we proceeded to the development of the instrument's adequacy. Then, the coordination with the house of studies was carried out. Finally, once the instrument was applied, data analysis was carried out with SPSS and Microsoft Excel programs. The data processing yielded frequency tables to analyze the results in the discussion and reach both conclusions and recommendations.
Data analysis method
The analysis of the collected data was done in three steps: first the validity and reliability tests of the instrument were performed using Cronbach's Alpha after the application of the pilot test in 20 students; then, through the statistical analysis in SPPS, the aptitude in each of the dimensions of the digital competence analyzed was analyzed. Finally, descriptive and inferential statistics were applied for both variables in each one of their dimensions; for the hypothesis test, chi-square was used.
RESULTS
The findings found in the study on sociodemographic factors associated with academic goals are presented.
Frecuency | Percentage | ||
Valid | Low | 686 | 49,0 |
Medium | 450 | 32,1 | |
Higher | 264 | 18,9 | |
Total | 1400 | 100,0 |
In Table 1, 49% of students had a low level, 32.1% had a medium level, and 18.9% had a high level of academic goals.
Levels | Learning Goals | Achievement goals | Social Reinforcement Goals | |||
f | % | f | % | F | % | |
Low | 691 | 49,4 | 662 | 47,3 | 662 | 47,3 |
Medium | 455 | 32,5 | 493 | 35,2 | 450 | 32,1 |
High | 254 | 18,1 | 245 | 17,5 | 288 | 20,6 |
Total | 1400 | 100,0 | 1400 | 100,0 | 1400 | 100,0 |
With regard to Table 2, 49.4% of students presented a low level; 32.5%, a medium level and 18.1%, a high level of learning goals; in achievement goals, 47.3% showed a low level, 35.2%, a medium level and 17.5%, a high level; in the social reinforcement goals dimension, 47.3% showed a low level, 32.1%, a medium level and 20.6% , a high level.
Metas académicas | Total | |||||
Low | Medium | High | ||||
Sex | Male | Recount %of the total | 324 | 184 | 151 | 659 |
% del total | 23,1% | 13,1% | 10,8% | 47,1% | ||
Female | Recount %of the total | 362 | 266 | 113 | 741 | |
25,9% | 19,0% | 8,1% | 52,9% | |||
Total | Recount %of the total | 686 | 450 | 264 | 1400 | |
49,0% | 32,1% | 18,9% | 100,0% |
In table 3, it was observed that, of the male sex regarding the academic goals variable, 23.1% presented a low level; 13.1%, a medium level and 10.8%, a high level; in relation to the female sex, 25.9% presented a low level; 19%, a medium level and 8.1%, a high level.
Academic goals | Total | |||||
Low | Medium | High | ||||
Age | >20 | Recount %of the total | 365 | 203 | 123 | 691 |
26,1% | 14,5% | 8,8% | 49,4% | |||
21-22 | Recount %of the total | 221 | 229 | 116 | 566 | |
15,8% | 16,4% | 8,3% | 40,4% | |||
<23 | Recount %of the total | 100 | 18 | 25 | 143 | |
7,1% | 1,3% | 1,8% | 10,2% | |||
Total | Recount %of the total | 686 | 450 | 264 | 1400 | |
49,0% | 32,1% | 18,9% | 100,0% |
In Table 4, students ages 20 and under accounted for 26.1% low, 14.5% medium, and 8.8% high; students ages 21-22 accounted for 15.8% low, 16.4% medium, and 8.3% high; and finally, students ages 23 and over accounted for 7.1% low, 1.3% medium, and 1.8% high.
Academics goals | Total | |||||
Low | Medium | High | ||||
School of origin | PublicPrivate | Recount %of the total | 389 | 133 | 125 | 647 |
27,8% | 9,5% | 8,9% | 46,2% | |||
Recount %of the total | 297 | 317 | 139 | 753 | ||
21,2% | 22,6% | 9,9% | 53,8% | |||
Total | Recount %of the total | 686 | 450 | 264 | 1400 | |
49,0% | 32,1% | 18,9% | 100,0% |
In Table 5, it was observed that of the students from public schools, 27.8% showed a low level; 9.5% showed a medium level and 8.9% a high level; of the students from private schools, 21.2% showed low levels; 22.6% showed a medium level and 9.9% a high level of academic goals.
Academics goals | Total | |||||
Low | Medium | High | ||||
Hours of study | >3 | Recount % of the total | 363 | 192 | 103 | 658 |
25,9% | 13,7% | 7,4% | 47,0% | |||
4-5 | Recount % of the total | 222 | 225 | 81 | 528 | |
15,9% | 16,1% | 5,8% | 37,7% | |||
<6 | Recount % of the total | 101 | 33 | 80 | 214 | |
7,2% | 2,4% | 5,7% | 15,3% | |||
Total | Recount % of the total | 686 | 450 | 264 | 1400 | |
49,0% | 32,1% | 18,9% | 100,0% |
In Table 6, it was observed that of the students that study from 3 to less hours, 25.9% showed a low level; 13.7% a medium level and 7.4% a high level; of those that study from 4 to 5 hours, 15.9% showed a low level; 16.1% a medium level and 5.8% a high level; finally, of those that study more than 6 hours, 7.2% showed a low level; 2.4% a medium level and 5.7% a high level.
Variables | Pearson Chi-square | Asymptotic Significance (bilateral) |
Sex | 17,775a | ,000 |
Age | 58,483a | ,000 |
School of origin | 80,753a | ,000 |
Hours of study | 94,879a | ,000 |
In table 7, the academic goals are associated with sex, age, school of origin, and hours of study as evidenced in the independence test (Chi-square x2 = 17,775ª, 58,483ª, 80,753ª, and 94,879ª respectively), and p< 0.05, so the alternate hypothesis is accepted and the null hypothesis is rejected; establishing that personal conditions are associated with the academic goals of students from a private university, 2020.
Variables | Pearson Chi-square | Asymptotic Significance (bilateral) |
Sex | 21,730a | ,000 |
Age | 42,618a | ,000 |
School of origin | 76,724a | ,000 |
Hours of study | 73,069a | ,000 |
In table 8, the learning goals are associated with sex, age, school of origin, and hours of study as evidenced in the independence test (Chi-square x2 = 21,730ª, 42,618ª, 76,724ª, and 73,069ª respectively), and p< 0.05, so the alternate hypothesis is accepted and the null hypothesis is rejected; establishing that personal conditions are associated with the learning goals of students in a private university, 2020.
Variables | Pearson Chi-square | Asymptotic Significance (bilateral) |
Sex | 5,706a | ,048 |
Age | 22,524a | ,000 |
School of origin | 44,616a | ,000 |
School of origin | 46,693a | ,000 |
In table 9, the achievement goals are associated with sex, age, school of origin, and hours of study as evidenced in the independence test (Chi-square x2 = 5,706a, 22,524a, 44,616a, and 46,693a respectively), and p<0.05, so the alternate hypothesis is accepted and the null hypothesis is rejected; establishing that personal conditions are associated with the achievement goals of students in a private university, 2020.
Variables | Pearson Chi-square | Asymptotic Significance (bilateral) |
Sex | 12,441a | ,002 |
Age | 55,744a | ,000 |
School of origin | 33,512a | ,000 |
School of origin | 89,667a | ,000 |
In table 10, the goals of social reinforcement are associated with sex, age, school of origin and hours of study as evidenced in the test of independence (Chi-square x2 = 12,441ª, 55,744ª, 33,512ª and 89,667ª respectively), and p< 0.05, so the alternate hypothesis is accepted and the null hypothesis is rejected; establishing that personal conditions are associated with the goals of social reinforcement of the students of a private university, 2020.
DISCUSSION
The objective of the study was to determine the association of sociodemographic factors in the dimensions (learning goals, achievement goals and social reinforcement goals) of the academic goals for a sample of university students in the Health career. The results indicate that 25.9% of the female students presented a low level, 19% a medium level, and 8.1% a high level of academic goals. These results coincide with Ruiz-Esteban's study (2018), which analyzed the evolution of academic goals and their influence on student performance in terms of sociodemographic variables (sex, age and academic year). The results showed that females had a significantly higher goal orientation than males of the same age. No definite motivational orientation was found in males, while females maintained an orientation toward achieving good academic results. Within the studies related to the variable sociodemographic factors, it has been possible to find the work of Chong (2017) that disagrees with the results of this research; the author concludes that, among the personal factors, the male sex has a greater incidence in academic performance than the female sex.
It is interesting that the greatest relative weight in the hours of study of the students are those who study from 3 to less hours given that 25.9% presented a low level; 13.7%, medium level and 7.4%, high level; of those who study from 4 to 5 hours, 15.9% showed a low level; 16.1%, medium level and 5.8%, high level; of those who study more than 6 hours, 7.2% showed a low level; 2.4%, medium level and 5.7%, high level. For Covarrubias & Acosta (2019), the following conclusions can be drawn from the results of this research: in university students at a public university, the greatest relative weight was found in learning goals, in the self-regulation of learning, indicating that students manage their study times, observe their behavior, seek help, and direct academic achievement toward learning rather than performance; as a novel result, planning, execution, and evaluation of their learning would have a greater influence than beliefs of effectiveness.
In this same line, Chávez et al. (2020) maintain that most people are immersed in a constant lack of time either at work, in the family or in study. It has been evidenced that there is an association between personal factors and the time needed by students to conclude academic activities. Among the factors considered in the study are the following: age, sex, and school of origin. These factors helped to emphasize that students not only have a bad organization of time; but also personal conditions such as emotional ones influence it.
The academic goals are associated with sex, age, school of origin, and hours of study of the students of a private university, 2020 put to the significance of p<0.05 and with each one of the dimensions (learning goal, social reinforcement goal, and achievement goals). Therefore, the studies of both Bakker & Demerouti (2013) and Ben & Linnenbrink (2015) agree that positive self-evaluations referring to the perception of personal capacities to control and influence the environment regulate the affective, cognitive and behavioral dimensions of university students for the achievement of academic goals.
On the other hand, Durán & Arias (2015) conclude that it is important to take into account the motivational factors in the first year of university studies and that these can be modified due to the adaptation of the individual and to factors that have to do with the university; therefore, it is important to develop research that includes more variables, not only of a motivational type, but also contextual and institutional, such as the graduation profile, curricular lines, among others.
CONCLUSION
It is concluded that sociodemographic factors influence academic goals in the way students perceive, interpret and react in the academic environment, resulting in different forms of approach, commitment and response to learning activities. It is recommended to carry out longitudinal studies with students of the first cycles and to compare them with those carried out five years after entering the university.
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Notas de autor
jpalaciosg@unmsm.edu.pe
Información adicional
How to cite: Garay, J. P. P., Flores, J. L. E., Calle, J. C. C., & Tamashiro-Tamashiro, J. (2021). Sociodemographic factors associated with academic goals in university students in times of the COVID-19 Pandemic. Revista Tempos e Espaços em Educação, 14(33), e15114. https://doi.org/10.20952/revtee.v14i33.15114
Authors' Contributions: Jessica Paola Palacios Garay: conception and design, analysis and interpretation of data. Jorge Luis Escalante Flores: acquisition of data, critical review of important intellectual content. Juan Carlos Chumacero Calle: acquisition of data, critical review of important intellectual content. Jaime Tamashiro-Tamashiro: drafting the article, critical review of important intellectual content. All authors have read and approved the final version of the manuscript.